Production plants for manufacturing containers (such as beverage cans) can produce a very large number of containers, with sophisticated (multicolor) decoration thereon, in a relatively short amount of time. For instance, a conventional decorator in a container production plant can decorate 2,000 containers per minute. Container decorations have intrinsic value, as consumers tend to attach perceptions of quality to a product based upon the design on the container that holds the product.
Conventionally, there is a lack of robust inspection of exterior surfaces of containers at these container production plants. A known process for container inspection is tasking an operator at the plant with periodically pulling containers from a conveyor for visual inspection. For instance, every so often (e.g., every 15 minutes), the operator may be tasked with pulling a small number of containers from the conveyor and visually inspecting the containers to ensure that the exterior surfaces of the containers are free of readily apparent defects (e.g., to ensure that proper colors are applied to the exterior surfaces of the containers, to ensure that the exterior surfaces of the containers are free of smears, etc.). Using this conventional approach, thousands of defective containers may be manufactured prior to the operator noticing a defect on the exterior surface of one or more of the sampled containers. In practice, these (completed) containers must be scrapped, resulting in significant cost to the container manufacturer.
Recently, automated systems have been developed and deployed in container production plants, wherein such systems are configured, through automated visual inspection, to detect defects on exterior surfaces of containers. These systems include multiple cameras that are positioned to capture images of exterior surfaces of a container when the container passes through an inspection region. In such systems, the images are captured while a container is illuminated by way of dark field illumination. Images of the sidewall of the container taken under dark field illumination are well-suited at depicting spatial defects, three-dimensional defects (e.g., dents, scuffs, contamination, etc.), and subtle color shifts in opaque inks on the container. A computing system analyzes the images captured by the cameras to determine whether the exterior surface of the container includes a defect. Systems that incorporate dark field illumination, however, are unable to accurately correlate measured color in the images to offline measurement systems and standards. Further, these systems are generally incapable of detecting, on containers that have been decorated with ink of dark colors, scratches or unintentional voids in decorations (where, for some reason, ink was not applied where it should have been applied).